big data file versus ram memory
On Dec 18, 2008, at 3:07 PM, Stephan Kolassa wrote:
Hi Mauricio, Mauricio Calvao schrieb:
1) I would like very much to use R for processing some big data files (around 1.7 or more GB) for spatial analysis, wavelets, and power spectra estimation; is this possible with R? Within IDL, such a big data set seems to be tractable...
There are some packages to handle large datasets, e.g., bigmemoRy. There were a couple of presentations on various ways to work with large datasets at the last useR conference - take a look at the presentations at http://www.statistik.uni-dortmund.de/useR-2008/ You'll probably be most interested in the "High Performance" streams.
2) I have heard/read that R "puts all its data on ram"? Does this really mean my data file cannot be bigger than my ram memory?
The philosophy is basically to use RAM. Anything working outside RAM is not exactly heretical to R, but it does require some additional effort.
3) If I have a big enough ram, would I be able to process whatever data set?? What constrains the practical limits of my data sets??
From what I understand - little to nothing, beyond the time needed for computations.
Er, ... it depends. At a minimum a person considering this should have read the FAQs. If this is a question about Windows, then R-Win FAQ 2.9: http://cran.r-project.org/bin/windows/base/rw-FAQ.html#There-seems-to-be-a-limit-on-the-memory-it-uses_0021 There has been quite a bit about this in the list over the last couple of years. Search the archives: http://search.r-project.org/
David Winsemius > > > HTH, > Stephan > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.